International Journal of Advanced Multidisciplinary Research and Studies
Volume 6, Issue 5, 2026
AI and Patient Safety - Trust but Verify: Safeguarding Patient Safety in the Age of AI Driven Nursing
Author(s): Pratik Ravindra Salve, Neha Michael-Salve
Abstract:
Artificial intelligence (AI) is reshaping patient safety by increasingly influencing clinical assessment, risk prediction, and nursing decision-making. Although AI-enabled systems offer opportunities to improve early detection, workflow efficiency, and clinical decision support, they also introduce risks associated with algorithmic bias, automation bias, limited contextual understanding, and misplaced confidence in machine-generated recommendations. These developments require a reconsideration of professional accountability and the evolving role of nurses in technology-mediated healthcare. This commentary examines the transition from conventional patient safety approaches towards an emerging paradigm in which safety is increasingly influenced by algorithmic intelligence. It argues that nurses must move beyond the operational use of AI to assume an active role in evaluating, interpreting, and governing its clinical influence. The concept of Verified Intelligence is proposed as a conceptual framework for integrating algorithmic capabilities with nursing expertise, ethical reasoning, contextual judgement, and person-centred care. Within this perspective, verification is positioned as an essential patient safety competency rather than an optional safeguard. The commentary further highlights implications for nursing education, continuing professional development, clinical leadership, and AI governance. Preparing nurses to critically assess AI-generated recommendations will be essential to maintaining human accountability and preventing avoidable harm. Ultimately, responsible AI integration requires a partnership in which technological intelligence supports, rather than supplants, professional judgement and patient advocacy.
Keywords: Artificial Intelligence, Patient Safety, Nursing Accountability, Clinical Decision Support
Pages: 1854-1857
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